Home | [1–10] << 11 12 13 14 15 >> |
Records | |||||
---|---|---|---|---|---|
Author | Jun Wan; Guodong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z Li | ||||
Title | Face Presentation Attack Detection (PAD) Challenges | Type | Book Chapter | ||
Year | 2023 | Publication | Advances in Face Presentation Attack Detection | Abbreviated Journal | |
Volume | Issue | Pages | 17–35 | ||
Keywords | |||||
Abstract | In recent years, the security of face recognition systems has been increasingly threatened. Face Anti-spoofing (FAS) is essential to secure face recognition systems primarily from various attacks. In order to attract researchers and push forward the state of the art in Face Presentation Attack Detection (PAD), we organized three editions of Face Anti-spoofing Workshop and Competition at CVPR 2019, CVPR 2020, and ICCV 2021, which have attracted more than 800 teams from academia and industry, and greatly promoted the algorithms to overcome many challenging problems. In this chapter, we introduce the detailed competition process, including the challenge phases, timeline and evaluation metrics. Along with the workshop, we will introduce the corresponding dataset for each competition including data acquisition details, data processing, statistics, and evaluation protocol. Finally, we provide the available link to download the datasets used in the challenges. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | SLCV | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | HUPBA | Approved | no | ||
Call Number | Admin @ si @ WGE2023b | Serial | 3956 | ||
Permanent link to this record | |||||
Author | Ernest Valveny; Oriol Ramos Terrades; Joan Mas; Marçal Rusiñol | ||||
Title | Interactive Document Retrieval and Classification. | Type | Book Chapter | ||
Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications | Abbreviated Journal | |
Volume | 48 | Issue | Pages | 17-30 | |
Keywords | |||||
Abstract | In this chapter we describe a system for document retrieval and classification following the interactive-predictive framework. In particular, the system addresses two different scenarios of document analysis: document classification based on visual appearance and logo detection. These two classical problems of document analysis are formulated following the interactive-predictive model, taking the user interaction into account to make easier the process of annotating and labelling the documents. A system implementing this model in a real scenario is presented and analyzed. This system also takes advantage of active learning techniques to speed up the task of labelling the documents. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Angel Sappa; Jordi Vitria | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
Area | Expedition | Conference | |||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ VRM2013 | Serial | 2341 | ||
Permanent link to this record | |||||
Author | Michal Drozdzal; Santiago Segui; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria | ||||
Title | An Application for Efficient Error-Free Labeling of Medical Images | Type | Book Chapter | ||
Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications | Abbreviated Journal | |
Volume | 48 | Issue | Pages | 1-16 | |
Keywords | |||||
Abstract | In this chapter we describe an application for efficient error-free labeling of medical images. In this scenario, the compilation of a complete training set for building a realistic model of a given class of samples is not an easy task, making the process tedious and time consuming. For this reason, there is a need for interactive labeling applications that minimize the effort of the user while providing error-free labeling. We propose a new algorithm that is based on data similarity in feature space. This method actively explores data in order to find the best label-aligned clustering and exploits it to reduce the labeler effort, that is measured by the number of “clicks. Moreover, error-free labeling is guaranteed by the fact that all data and their labels proposals are visually revised by en expert. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
Area | Expedition | Conference | |||
Notes | MILAB; OR;MV | Approved | no | ||
Call Number | Admin @ si @ DSR2013 | Serial | 2235 | ||
Permanent link to this record | |||||
Author | Jorge Bernal; Fernando Vilariño; F. Javier Sanchez | ||||
Title | Towards Intelligent Systems for Colonoscopy | Type | Book Chapter | ||
Year | 2011 | Publication | Colonoscopy | Abbreviated Journal | |
Volume | 1 | Issue | Pages | 257-282 | |
Keywords | |||||
Abstract | In this chapter we present tools that can be used to build intelligent systems for colonoscopy.
The idea is, by using methods based on computer vision and artificial intelligence, add significant value to the colonoscopy procedure. Intelligent systems are being used to assist in other medical interventions |
||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Intech | Place of Publication | Editor | Paul Miskovitz | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-953-307-568-6 | Medium | ||
Area | 800 | Expedition | Conference | ||
Notes | MV;SIAI | Approved | no | ||
Call Number | IAM @ iam @ BVS2011 | Serial | 1697 | ||
Permanent link to this record | |||||
Author | Svebor Karaman; Giuseppe Lisanti; Andrew Bagdanov; Alberto del Bimbo | ||||
Title | From re-identification to identity inference: Labeling consistency by local similarity constraints | Type | Book Chapter | ||
Year | 2014 | Publication | Person Re-Identification | Abbreviated Journal | |
Volume | 2 | Issue | Pages | 287-307 | |
Keywords | re-identification; Identity inference; Conditional random fields; Video surveillance | ||||
Abstract | In this chapter, we introduce the problem of identity inference as a generalization of person re-identification. It is most appropriate to distinguish identity inference from re-identification in situations where a large number of observations must be identified without knowing a priori that groups of test images represent the same individual. The standard single- and multishot person re-identification common in the literature are special cases of our formulation. We present an approach to solving identity inference by modeling it as a labeling problem in a Conditional Random Field (CRF). The CRF model ensures that the final labeling gives similar labels to detections that are similar in feature space. Experimental results are given on the ETHZ, i-LIDS and CAVIAR datasets. Our approach yields state-of-the-art performance for multishot re-identification, and our results on the more general identity inference problem demonstrate that we are able to infer the identity of very many examples even with very few labeled images in the gallery. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer London | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2191-6586 | ISBN | 978-1-4471-6295-7 | Medium | |
Area | Expedition | Conference | |||
Notes | LAMP; 600.079 | Approved | no | ||
Call Number | Admin @ si @KLB2014b | Serial | 2521 | ||
Permanent link to this record | |||||
Author | Salim Jouili; Salvatore Tabbone; Ernest Valveny | ||||
Title | Comparing Graph Similarity Measures for Graphical Recognition | Type | Book Chapter | ||
Year | 2010 | Publication | Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers | Abbreviated Journal | |
Volume | 6020 | Issue | Pages | 37-48 | |
Keywords | |||||
Abstract | In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-13727-3 | Medium | |
Area | Expedition | Conference | GREC | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ JTV2010 | Serial | 2404 | ||
Permanent link to this record | |||||
Author | Lluis Pere de las Heras; Oriol Ramos Terrades; Josep Llados | ||||
Title | Ontology-Based Understanding of Architectural Drawings | Type | Book Chapter | ||
Year | 2017 | Publication | International Workshop on Graphics Recognition. GREC 2015.Graphic Recognition. Current Trends and Challenges | Abbreviated Journal | |
Volume | 9657 | Issue | Pages | 75-85 | |
Keywords | Graphics recognition; Floor plan analysi; Domain ontology | ||||
Abstract | In this paper we present a knowledge base of architectural documents aiming at improving existing methods of floor plan classification and understanding. It consists of an ontological definition of the domain and the inclusion of real instances coming from both, automatically interpreted and manually labeled documents. The knowledge base has proven to be an effective tool to structure our knowledge and to easily maintain and upgrade it. Moreover, it is an appropriate means to automatically check the consistency of relational data and a convenient complement of hard-coded knowledge interpretation systems. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | DAG; 600.121 | Approved | no | ||
Call Number | Admin @ si @ HRL2017 | Serial | 3086 | ||
Permanent link to this record | |||||
Author | Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados | ||||
Title | Spotting Graphical Symbols in Camera-Acquired Documents in Real Time | Type | Book Chapter | ||
Year | 2014 | Publication | Graphics Recognition. Current Trends and Challenges | Abbreviated Journal | |
Volume | 8746 | Issue | Pages | 3-10 | |
Keywords | |||||
Abstract | In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Bart Lamiroy; Jean-Marc Ogier | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-662-44853-3 | Medium | |
Area | Expedition | Conference | |||
Notes | DAG; 600.045; 600.055; 600.061; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RKL2014 | Serial | 2700 | ||
Permanent link to this record | |||||
Author | Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez | ||||
Title | Unsupervised and Notation-Independent Wall Segmentation in Floor Plans Using a Combination of Statistical and Structural Strategies | Type | Book Chapter | ||
Year | 2014 | Publication | Graphics Recognition. Current Trends and Challenges | Abbreviated Journal | |
Volume | 8746 | Issue | Pages | 109-121 | |
Keywords | Graphics recognition; Floor plan analysis; Object segmentation | ||||
Abstract | In this paper we present a wall segmentation approach in floor plans that is able to work independently to the graphical notation, does not need any pre-annotated data for learning, and is able to segment multiple-shaped walls such as beams and curved-walls. This method results from the combination of the wall segmentation approaches [3, 5] presented recently by the authors. Firstly, potential straight wall segments are extracted in an unsupervised way similar to [3], but restricting even more the wall candidates considered in the original approach. Then, based on [5], these segments are used to learn the texture pattern of walls and spot the lost instances. The presented combination of both methods has been tested on 4 available datasets with different notations and compared qualitatively and quantitatively to the state-of-the-art applied on these collections. Additionally, some qualitative results on floor plans directly downloaded from the Internet are reported in the paper. The overall performance of the method demonstrates either its adaptability to different wall notations and shapes, and to document qualities and resolutions. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-662-44853-3 | Medium | |
Area | Expedition | Conference | |||
Notes | DAG; ADAS; 600.076; 600.077 | Approved | no | ||
Call Number | Admin @ si @ HVS2014 | Serial | 2535 | ||
Permanent link to this record | |||||
Author | Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman | ||||
Title | A Performance Characterization Algorithm for Symbol Localization | Type | Book Chapter | ||
Year | 2010 | Publication | Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers | Abbreviated Journal | |
Volume | 6020 | Issue | Pages | 260–271 | |
Keywords | |||||
Abstract | In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols). | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-13727-3 | Medium | |
Area | Expedition | Conference | GREC | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ DRV2010 | Serial | 2406 | ||
Permanent link to this record | |||||
Author | Marc Castello; Jordi Gonzalez; Ariel Amato; Pau Baiget; Carles Fernandez; Josep M. Gonfaus; Ramon Mollineda; Marco Pedersoli; Nicolas Perez de la Blanca; Xavier Roca | ||||
Title | Exploiting Multimodal Interaction Techniques for Video-Surveillance | Type | Book Chapter | ||
Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications Intelligent Systems Reference Library | Abbreviated Journal | |
Volume | 48 | Issue | 8 | Pages | 135-151 |
Keywords | |||||
Abstract | In this paper we present an example of a video surveillance application that exploits Multimodal Interactive (MI) technologies. The main objective of the so-called VID-Hum prototype was to develop a cognitive artificial system for both the detection and description of a particular set of human behaviours arising from real-world events. The main procedure of the prototype described in this chapter entails: (i) adaptation, since the system adapts itself to the most common behaviours (qualitative data) inferred from tracking (quantitative data) thus being able to recognize abnormal behaviors; (ii) feedback, since an advanced interface based on Natural Language understanding allows end-users the communicationwith the prototype by means of conceptual sentences; and (iii) multimodality, since a virtual avatar has been designed to describe what is happening in the scene, based on those textual interpretations generated by the prototype. Thus, the MI methodology has provided an adequate framework for all these cooperating processes. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
Area | Expedition | Conference | |||
Notes | ISE; 605.203; 600.049 | Approved | no | ||
Call Number | CGA2013 | Serial | 2222 | ||
Permanent link to this record | |||||
Author | Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados | ||||
Title | Symbol Recognition Using a Concept Lattice of Graphical Patterns | Type | Book Chapter | ||
Year | 2010 | Publication | Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers | Abbreviated Journal | |
Volume | 6020 | Issue | Pages | 187-198 | |
Keywords | |||||
Abstract | In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-13727-3 | Medium | |
Area | Expedition | Conference | |||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ RBO2010 | Serial | 2407 | ||
Permanent link to this record | |||||
Author | Bogdan Raducanu; Fadi Dornaika | ||||
Title | A Discriminative Non-Linear Manifold Learning Technique for Face Recognition | Type | Book Chapter | ||
Year | 2011 | Publication | Informatics Engineering and Information Science | Abbreviated Journal | |
Volume | 254 | Issue | 6 | Pages | 339-353 |
Keywords | |||||
Abstract | In this paper we propose a novel non-linear discriminative analysis technique for manifold learning. The proposed approach is a discriminant version of Laplacian Eigenmaps which takes into account the class label information in order to guide the procedure of non-linear dimensionality reduction. By following the large margin concept, the graph Laplacian is split in two components: within-class graph and between-class graph to better characterize the discriminant property of the data.
Our approach has been tested on several challenging face databases and it has been conveniently compared with other linear and non-linear techniques. The experimental results confirm that our method outperforms, in general, the existing ones. Although we have concentrated in this paper on the face recognition problem, the proposed approach could also be applied to other category of objects characterized by large variance in their appearance. |
||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1865-0929 | ISBN | 978-3-642-25482-6 | Medium | |
Area | Expedition | Conference | ICIEIS | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ RaD2011 | Serial | 1804 | ||
Permanent link to this record | |||||
Author | E. Tavalera; Mariella Dimiccoli; Marc Bolaños; Maedeh Aghaei; Petia Radeva | ||||
Title | Regularized Clustering for Egocentric Video Segmentation | Type | Book Chapter | ||
Year | 2015 | Publication | Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | Issue | Pages | 327-336 | ||
Keywords | Temporal video segmentation ; Egocentric videos ; Clustering | ||||
Abstract | In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energyminimization framework. Given the tendency of most AC methods to oversegment video sequences when clustering their frames, we combine the clustering with a concept drift detection technique (ADWIN) that has rigorous guarantee of performances. ADWIN serves as a statistical upper bound for the clustering-based video segmentation. We integrate techniques in an energy-minimization framework that serves disambiguate the decision of both techniques and to complete the segmentation taking into account the temporal continuity of video frames We present experiments over egocentric sets of more than 13.000 images acquired with different wearable cameras, showing that our method outperforms state-of-the-art clustering methods. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer International Publishing | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-3-319-19390-8 | Medium | ||
Area | Expedition | Conference | |||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @TDB2015a | Serial | 2781 | ||
Permanent link to this record | |||||
Author | Maryam Asadi-Aghbolaghi; Albert Clapes; Marco Bellantonio; Hugo Jair Escalante; Victor Ponce; Xavier Baro; Isabelle Guyon; Shohreh Kasaei; Sergio Escalera | ||||
Title | Deep Learning for Action and Gesture Recognition in Image Sequences: A Survey | Type | Book Chapter | ||
Year | 2017 | Publication | Gesture Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 539-578 | ||
Keywords | Action recognition; Gesture recognition; Deep learning architectures; Fusion strategies | ||||
Abstract | Interest in automatic action and gesture recognition has grown considerably in the last few years. This is due in part to the large number of application domains for this type of technology. As in many other computer vision areas, deep learning based methods have quickly become a reference methodology for obtaining state-of-the-art performance in both tasks. This chapter is a survey of current deep learning based methodologies for action and gesture recognition in sequences of images. The survey reviews both fundamental and cutting edge methodologies reported in the last few years. We introduce a taxonomy that summarizes important aspects of deep learning for approaching both tasks. Details of the proposed architectures, fusion strategies, main datasets, and competitions are reviewed. Also, we summarize and discuss the main works proposed so far with particular interest on how they treat the temporal dimension of data, their highlighting features, and opportunities and challenges for future research. To the best of our knowledge this is the first survey in the topic. We foresee this survey will become a reference in this ever dynamic field of research. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | HUPBA; no proj | Approved | no | ||
Call Number | Admin @ si @ ACB2017a | Serial | 2981 | ||
Permanent link to this record |